{"id":"https://openalex.org/W2963605190","doi":"https://doi.org/10.18653/v1/p16-1169","title":"Learning Concept Taxonomies from Multi-modal Data","display_name":"Learning Concept Taxonomies from Multi-modal Data","publication_year":2016,"publication_date":"2016-01-01","ids":{"openalex":"https://openalex.org/W2963605190","doi":"https://doi.org/10.18653/v1/p16-1169","mag":"2963605190"},"language":"en","primary_location":{"id":"doi:10.18653/v1/p16-1169","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/p16-1169","pdf_url":"https://www.aclweb.org/anthology/P16-1169.pdf","source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 54th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)","raw_type":"proceedings-article"},"type":"preprint","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.aclweb.org/anthology/P16-1169.pdf","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5100397026","display_name":"Hao Zhang","orcid":"https://orcid.org/0000-0003-1991-119X"},"institutions":[{"id":"https://openalex.org/I74973139","display_name":"Carnegie Mellon University","ror":"https://ror.org/05x2bcf33","country_code":"US","type":"education","lineage":["https://openalex.org/I74973139"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Hao Zhang","raw_affiliation_strings":["Carnegie Mellon University,"],"affiliations":[{"raw_affiliation_string":"Carnegie Mellon University,","institution_ids":["https://openalex.org/I74973139"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5085608858","display_name":"Zhiting Hu","orcid":"https://orcid.org/0000-0002-6239-5031"},"institutions":[{"id":"https://openalex.org/I74973139","display_name":"Carnegie Mellon University","ror":"https://ror.org/05x2bcf33","country_code":"US","type":"education","lineage":["https://openalex.org/I74973139"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Zhiting Hu","raw_affiliation_strings":["Carnegie Mellon University,"],"affiliations":[{"raw_affiliation_string":"Carnegie Mellon University,","institution_ids":["https://openalex.org/I74973139"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5088888805","display_name":"Yuntian Deng","orcid":"https://orcid.org/0000-0002-1257-1797"},"institutions":[{"id":"https://openalex.org/I74973139","display_name":"Carnegie Mellon University","ror":"https://ror.org/05x2bcf33","country_code":"US","type":"education","lineage":["https://openalex.org/I74973139"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Yuntian Deng","raw_affiliation_strings":["Carnegie Mellon University,"],"affiliations":[{"raw_affiliation_string":"Carnegie Mellon University,","institution_ids":["https://openalex.org/I74973139"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5002316432","display_name":"Mrinmaya Sachan","orcid":"https://orcid.org/0000-0001-8787-8681"},"institutions":[{"id":"https://openalex.org/I74973139","display_name":"Carnegie Mellon University","ror":"https://ror.org/05x2bcf33","country_code":"US","type":"education","lineage":["https://openalex.org/I74973139"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Mrinmaya Sachan","raw_affiliation_strings":["Carnegie Mellon University,"],"affiliations":[{"raw_affiliation_string":"Carnegie Mellon University,","institution_ids":["https://openalex.org/I74973139"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5002869474","display_name":"Zhicheng Yan","orcid":"https://orcid.org/0000-0002-6290-9848"},"institutions":[{"id":"https://openalex.org/I308392441","display_name":"International University of the Caribbean","ror":"https://ror.org/02rv57d03","country_code":"JM","type":"education","lineage":["https://openalex.org/I308392441"]}],"countries":["JM"],"is_corresponding":false,"raw_author_name":"Zhicheng Yan","raw_affiliation_strings":["UIUC"],"affiliations":[{"raw_affiliation_string":"UIUC","institution_ids":["https://openalex.org/I308392441"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5009547049","display_name":"Eric P. Xing","orcid":"https://orcid.org/0009-0005-9158-4201"},"institutions":[{"id":"https://openalex.org/I74973139","display_name":"Carnegie Mellon University","ror":"https://ror.org/05x2bcf33","country_code":"US","type":"education","lineage":["https://openalex.org/I74973139"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Eric Xing","raw_affiliation_strings":["Carnegie Mellon University,"],"affiliations":[{"raw_affiliation_string":"Carnegie Mellon University,","institution_ids":["https://openalex.org/I74973139"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5100397026"],"corresponding_institution_ids":["https://openalex.org/I74973139"],"apc_list":null,"apc_paid":null,"fwci":1.3515,"has_fulltext":true,"cited_by_count":18,"citation_normalized_percentile":{"value":0.87760648,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":97},"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11439","display_name":"Video Analysis and Summarization","score":0.9940000176429749,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T11439","display_name":"Video Analysis and Summarization","score":0.9940000176429749,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11714","display_name":"Multimodal Machine Learning Applications","score":0.9934999942779541,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10824","display_name":"Image Retrieval and Classification Techniques","score":0.9930999875068665,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8558605909347534},{"id":"https://openalex.org/keywords/taxonomy","display_name":"Taxonomy (biology)","score":0.6539711952209473},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6392974257469177},{"id":"https://openalex.org/keywords/wordnet","display_name":"WordNet","score":0.6074044108390808},{"id":"https://openalex.org/keywords/encode","display_name":"ENCODE","score":0.5947149395942688},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.556977391242981},{"id":"https://openalex.org/keywords/modal","display_name":"Modal","score":0.546855628490448},{"id":"https://openalex.org/keywords/semantics","display_name":"Semantics (computer science)","score":0.485897958278656},{"id":"https://openalex.org/keywords/probabilistic-logic","display_name":"Probabilistic logic","score":0.42618119716644287},{"id":"https://openalex.org/keywords/information-retrieval","display_name":"Information retrieval","score":0.3916497230529785},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3273080885410309}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8558605909347534},{"id":"https://openalex.org/C58642233","wikidata":"https://www.wikidata.org/wiki/Q8269924","display_name":"Taxonomy (biology)","level":2,"score":0.6539711952209473},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6392974257469177},{"id":"https://openalex.org/C157659113","wikidata":"https://www.wikidata.org/wiki/Q533822","display_name":"WordNet","level":2,"score":0.6074044108390808},{"id":"https://openalex.org/C66746571","wikidata":"https://www.wikidata.org/wiki/Q1134833","display_name":"ENCODE","level":3,"score":0.5947149395942688},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.556977391242981},{"id":"https://openalex.org/C71139939","wikidata":"https://www.wikidata.org/wiki/Q910194","display_name":"Modal","level":2,"score":0.546855628490448},{"id":"https://openalex.org/C184337299","wikidata":"https://www.wikidata.org/wiki/Q1437428","display_name":"Semantics (computer science)","level":2,"score":0.485897958278656},{"id":"https://openalex.org/C49937458","wikidata":"https://www.wikidata.org/wiki/Q2599292","display_name":"Probabilistic logic","level":2,"score":0.42618119716644287},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.3916497230529785},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3273080885410309},{"id":"https://openalex.org/C59822182","wikidata":"https://www.wikidata.org/wiki/Q441","display_name":"Botany","level":1,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C188027245","wikidata":"https://www.wikidata.org/wiki/Q750446","display_name":"Polymer chemistry","level":1,"score":0.0},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.0},{"id":"https://openalex.org/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.18653/v1/p16-1169","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/p16-1169","pdf_url":"https://www.aclweb.org/anthology/P16-1169.pdf","source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 54th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.18653/v1/p16-1169","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/p16-1169","pdf_url":"https://www.aclweb.org/anthology/P16-1169.pdf","source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 54th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)","raw_type":"proceedings-article"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/10","score":0.7400000095367432,"display_name":"Reduced inequalities"}],"awards":[{"id":"https://openalex.org/G1081469516","display_name":null,"funder_award_id":"IIS1447676","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G8533660586","display_name":"BIGDATA: F: DKA: Collaborative Research: Theory and Algorithms for Parallel Probabilistic Inference with Big Data, via Big Model, in Realistic Distributed Computing Environments","funder_award_id":"1447676","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"}],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"},{"id":"https://openalex.org/F4320309480","display_name":"Nvidia","ror":"https://ror.org/03jdj4y14"}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2963605190.pdf","grobid_xml":"https://content.openalex.org/works/W2963605190.grobid-xml"},"referenced_works_count":39,"referenced_works":["https://openalex.org/W38703128","https://openalex.org/W64813323","https://openalex.org/W304239299","https://openalex.org/W841113906","https://openalex.org/W1686810756","https://openalex.org/W1847921443","https://openalex.org/W1851597118","https://openalex.org/W1964763677","https://openalex.org/W1995006620","https://openalex.org/W2081580037","https://openalex.org/W2096315187","https://openalex.org/W2097123411","https://openalex.org/W2100132811","https://openalex.org/W2108598243","https://openalex.org/W2112184938","https://openalex.org/W2116339064","https://openalex.org/W2124033848","https://openalex.org/W2134665698","https://openalex.org/W2143042756","https://openalex.org/W2144108169","https://openalex.org/W2145056192","https://openalex.org/W2148780922","https://openalex.org/W2153579005","https://openalex.org/W2155734303","https://openalex.org/W2162683784","https://openalex.org/W2168565044","https://openalex.org/W2247119764","https://openalex.org/W2250742840","https://openalex.org/W2251109971","https://openalex.org/W2251168605","https://openalex.org/W2251291469","https://openalex.org/W2251905138","https://openalex.org/W2289324734","https://openalex.org/W2611669587","https://openalex.org/W2950276680","https://openalex.org/W2951714314","https://openalex.org/W2962860144","https://openalex.org/W4294170691","https://openalex.org/W4386506836"],"related_works":["https://openalex.org/W2900382651","https://openalex.org/W1981879262","https://openalex.org/W2363417484","https://openalex.org/W4225863708","https://openalex.org/W1480103567","https://openalex.org/W1599970036","https://openalex.org/W1849827364","https://openalex.org/W2786299737","https://openalex.org/W2121846020","https://openalex.org/W1572864191"],"abstract_inverted_index":{"We":[0,95],"study":[1],"the":[2,21,102],"problem":[3],"of":[4,59,72,78,87],"automatically":[5],"building":[6,79],"hypernym":[7],"taxonomies":[8,81],"from":[9,82],"textual":[10],"and":[11,44,61,75,99],"visual":[12,24],"data.":[13],"Previous":[14],"works":[15],"in":[16],"taxonomy":[17,38],"induction":[18,39],"generally":[19],"ignore":[20],"increasingly":[22],"prominent":[23],"data,":[25],"which":[26],"encode":[27],"important":[28],"perceptual":[29],"semantics.":[30],"Instead,":[31],"we":[32,51],"propose":[33],"a":[34,69,85,112],"probabilistic":[35],"model":[36,64,98],"for":[37,84],"by":[40,111],"jointly":[41],"leveraging":[42],"text":[43],"images.":[45,94],"To":[46],"avoid":[47],"hand-crafted":[48],"feature":[49],"engineering,":[50],"design":[52],"end-to-end":[53],"features":[54,100],"based":[55],"on":[56,101],"distributed":[57],"representations":[58],"images":[60],"words.":[62],"The":[63],"is":[65,76],"discriminatively":[66],"trained":[67],"given":[68],"small":[70],"set":[71],"existing":[73],"ontologies":[74],"capable":[77],"full":[80],"scratch":[83],"collection":[86],"unseen":[88],"conceptual":[89],"label":[90],"items":[91],"with":[92],"associated":[93],"evaluate":[96],"our":[97,106],"WordNet":[103],"hierarchies,":[104],"where":[105],"system":[107],"outperforms":[108],"previous":[109],"approaches":[110],"large":[113],"gap.":[114]},"counts_by_year":[{"year":2024,"cited_by_count":2},{"year":2022,"cited_by_count":2},{"year":2021,"cited_by_count":3},{"year":2020,"cited_by_count":3},{"year":2019,"cited_by_count":1},{"year":2018,"cited_by_count":3},{"year":2017,"cited_by_count":2},{"year":2016,"cited_by_count":2}],"updated_date":"2026-04-10T15:06:20.359241","created_date":"2025-10-10T00:00:00"}